There’s no denying that artificial intelligence and machine learning are drawing a lot of buzz. Company CEOs brag about integrating A.I. and machine-learning algorithms into their products and internal tech stacks; researchers predict that “smart” systems will soon supplant human workers in certain industries; and tech pros are dropping as many A.I.-related terms into their résumés as possible. Given all that momentum, it behooves tech pros to learn as much as they can about the practical applications of artificial intelligence. And what better teacher than Andrew Ng, the founder and former lead of Google Brain (the search engine giant’s deep learning project) and former chief scientist of Baidu? A few years ago, Ng started a machine-learning class at Coursera, the online-learning hub he co-founded. Now he’s back with a Deep Learning unit (deeplearning.ai). If you ever wanted to build a neural network, run a machine-learning project, or learn how A.I. is used in sub-industries such as autonomous driving and healthcare, now’s your chance. Technologies used in the unit, which consists of five courses, include Python and TensorFlow. The first course requires an estimated four weeks of study, at 3-6 hours per week; the second course, three weeks; and the third course, two weeks. The final two courses, Convolutional Neural Networks and Sequence Models, do not have a timeframe in Coursera’s catalog. “Just as every new CS graduate now knows how to use the Cloud, every programmer in the future must know how to use AI,” Ng wrote in a posting on Coursera’s blog. “There are millions of ways Deep Learning can be used to improve human life, so society needs millions of you from all around the world to build great AI systems.” For those interested in participating, there are a number of perquisites. Specifically, students must have intermediate Python programming skills, as well as knowledge of loops, control flows, data structures, files, and functions. Coursera recommends prior experience with PyData libraries (such as Numpy and Pandas), along with an understanding of how to frame machine-learning problems. And Ng is right: demand for tech pros well-versed in machine learning will likely outstrip demand for some time to come. Data suggests those with highly specialized A.I. skills can name their price on the open market. New A.I. Course Focuses on Deep Learning
There’s no denying that artificial intelligence and machine learning are drawing a lot of buzz. Company CEOs brag about integrating A.I. and machine-learning algorithms into their products and internal tech stacks; researchers predict that “smart” systems will soon supplant human workers in certain industries; and tech pros are dropping as many A.I.-related terms into their résumés as possible. Given all that momentum, it behooves tech pros to learn as much as they can about the practical applications of artificial intelligence. And what better teacher than Andrew Ng, the founder and former lead of Google Brain (the search engine giant’s deep learning project) and former chief scientist of Baidu? A few years ago, Ng started a machine-learning class at Coursera, the online-learning hub he co-founded. Now he’s back with a Deep Learning unit (deeplearning.ai). If you ever wanted to build a neural network, run a machine-learning project, or learn how A.I. is used in sub-industries such as autonomous driving and healthcare, now’s your chance. Technologies used in the unit, which consists of five courses, include Python and TensorFlow. The first course requires an estimated four weeks of study, at 3-6 hours per week; the second course, three weeks; and the third course, two weeks. The final two courses, Convolutional Neural Networks and Sequence Models, do not have a timeframe in Coursera’s catalog. “Just as every new CS graduate now knows how to use the Cloud, every programmer in the future must know how to use AI,” Ng wrote in a posting on Coursera’s blog. “There are millions of ways Deep Learning can be used to improve human life, so society needs millions of you from all around the world to build great AI systems.” For those interested in participating, there are a number of perquisites. Specifically, students must have intermediate Python programming skills, as well as knowledge of loops, control flows, data structures, files, and functions. Coursera recommends prior experience with PyData libraries (such as Numpy and Pandas), along with an understanding of how to frame machine-learning problems. And Ng is right: demand for tech pros well-versed in machine learning will likely outstrip demand for some time to come. Data suggests those with highly specialized A.I. skills can name their price on the open market. 
